Testing hypotheses about fecundity, body size and maternal condition in fishes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Recent research suggests that maternal condition positively influences the number of eggs spawned in fishes. These studies commonly choose a priori to use body length rather than weight as an explanatory variable of offspring production, even though weight is usually the better predictor of fecundity. We are concerned that consistent exclusion of body weight as a predictor of egg production inflates the variance in fecundity attributable to maternal condition. By analysing data on three populations of Atlantic cod ( Gadus morhua , Gadidae) and 10 populations of brook trout ( Salvelinus fontinalis , Salmonidae), we illustrate the need for a statistically defensible method of model selection to distinguish the effects of maternal condition on egg production from the effects of body size alone. Forward stepwise regression and null model analyses reveal how length‐based regressions can significantly over‐estimate correlations between condition and fecundity, leading us to conclude that the effect of condition on egg productivity may not be as ubiquitous or as biologically important as previously thought. Our work underscores the need for greater statistical clarity in analyses of the effects of maternal condition on reproductive productivity in fishes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it